US20020181390A1 - Estimating channel parameters in multi-input, multi-output (MIMO) systems - Google Patents
Estimating channel parameters in multi-input, multi-output (MIMO) systems Download PDFInfo
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- US20020181390A1 US20020181390A1 US10/128,756 US12875602A US2002181390A1 US 20020181390 A1 US20020181390 A1 US 20020181390A1 US 12875602 A US12875602 A US 12875602A US 2002181390 A1 US2002181390 A1 US 2002181390A1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L25/00—Baseband systems
- H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines
- H04L25/0202—Channel estimation
- H04L25/0224—Channel estimation using sounding signals
- H04L25/0226—Channel estimation using sounding signals sounding signals per se
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/02—Arrangements for detecting or preventing errors in the information received by diversity reception
- H04L1/06—Arrangements for detecting or preventing errors in the information received by diversity reception using space diversity
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/20—Arrangements for detecting or preventing errors in the information received using signal quality detector
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/26—Systems using multi-frequency codes
- H04L27/2601—Multicarrier modulation systems
- H04L27/2602—Signal structure
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04B—TRANSMISSION
- H04B7/00—Radio transmission systems, i.e. using radiation field
- H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
- H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
- H04B7/0413—MIMO systems
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/004—Arrangements for detecting or preventing errors in the information received by using forward error control
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/26—Systems using multi-frequency codes
- H04L27/2601—Multicarrier modulation systems
- H04L27/2602—Signal structure
- H04L27/26035—Maintenance of orthogonality, e.g. for signals exchanged between cells or users, or by using covering codes or sequences
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L27/00—Modulated-carrier systems
- H04L27/26—Systems using multi-frequency codes
- H04L27/2601—Multicarrier modulation systems
- H04L27/2647—Arrangements specific to the receiver only
Definitions
- the present invention is generally related to wireless communication systems that employ Orthogonal Frequency Division Multiplexing (OFDM). More particularly, the present invention is related to an apparatus and method for estimating channel parameters in a Multi-Input, Multi-Output (MIMO) OFDM system.
- OFDM Orthogonal Frequency Division Multiplexing
- Frequency Division Multiplexing the frequency spectrum is divided into sub-channels.
- Information e.g. voice, video, audio, text, etc.
- FDM Frequency Division Multiplexing
- OFDM Orthogonal Frequency Division Multiplexing
- OFDM technologies are typically divided into two categories.
- the first category is the Single-Input, Single-Output (SISO) scheme, which utilizes a single transmitting antenna to transmit radio frequency (RF) signals and a single receiving antenna to receive the RF signals.
- the second category is the Multi-Input, Multi-Output (MIMO) scheme, which uses multiple transmitting antennas and multiple receiving antennas.
- SISO Single-Input, Single-Output
- MIMO Multi-Input, Multi-Output
- training symbols or preamble, at the beginning of data frames, are usually added as a prefix to the data symbols.
- the data symbols include the useful data or information (e.g., voice, data, video, etc.), which is meant to be transmitted to a remote location.
- the training symbols in SISO systems are used to provide synchronization of the received signals with respect to the transmitted signals, as well as to provide channel parameter estimation.
- the present invention provides systems and methods that overcome the deficiencies of the prior art as mentioned above.
- the present invention utilizes a sequence of training symbols or preambles that may be used in both Single-Input, Single-Output (SISO) and Multi-Input, Multi-Output (MIMO) systems, using any number of transmitting and receiving antennas.
- An embodiment of the present invention comprises an apparatus that can be used to estimate channel parameters across which a data frame is transmitted in a MIMO system.
- the parameter estimator calculates an accurate estimation of the characteristics of the channel, thereby making the MIMO systems operational.
- the present invention achieves an accurate estimation of channel parameters and further achieves synchronization in the time domain and frequency domain and, therefore, enables MIMO systems to operate acceptably.
- One MIMO Orthogonal Frequency Division Multiplexing (OFDM) system of the present invention includes a number of OFDM modulators, which provide data frames to be transmitted across a channel.
- the data frames of the present invention comprise one or more training symbols, a plurality of data symbols, and cyclic prefixes inserted between the data symbols.
- a number of transmitting antennas corresponding to the number of modulators are used to transmit the modulated signals over the channel.
- a number of receiving antennas are used to receive the transmitted signals.
- the received signals are demodulated by a number of OFDM demodulators corresponding to the number of receiving antennas and decoded by an OFDM decoder, which processes the data frames.
- the MIMO system of the present invention is capable of providing time and frequency synchronization as well as perform channel estimation.
- a method of the present invention is also provided, wherein parameter estimation is carried out in a MIMO system.
- the method includes producing data frames comprising at least one training symbol, multiple data symbols and cyclic prefixes.
- the data frames are transmitted over the channel, received, demodulated, and processed.
- an estimation of the parameters of the channel may be achieved from the data frame.
- FIG. 1 is a block diagram illustrating an example embodiment of a Multi-Input, Multi-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) system.
- MIMO Multi-Input, Multi-Output
- OFDM Orthogonal Frequency Division Multiplexing
- FIG. 2 is a block diagram illustrating an example embodiment of the MIMO encoder shown in FIG. 1.
- FIG. 3 is a block diagram illustrating an example embodiment of one of the OFDM modulators shown in FIG. 1.
- FIG. 4 illustrates an example frame structure for a MIMO OFDM system.
- FIG. 5 is a block diagram illustrating an example matrix of a transmitted sequence structure and an example matrix of a received sequence structure using the modulator/demodulator arrangement shown in FIG. 1.
- FIG. 6 illustrates a three-dimensional representation of the received sequence structure in detail.
- FIG. 7 is a block diagram illustrating an example embodiment of one of the OFDM demodulators shown in FIG. 1.
- FIG. 8 is a block diagram illustrating an example embodiment of the decoder shown in FIG. 1.
- FIG. 9 is a flow chart of a first embodiment of a method for calculating fine channel estimates.
- FIG. 10 is a flow chart of a second embodiment of a method for calculating fine channel estimates.
- FIG. 11 is a flow chart of an example embodiment of a method for calculating noise variance estimates when the signal transmission matrices are unitary.
- FIG. 12 is a flow chart of an example embodiment of a method for calculating noise variance estimates when the signal transmission matrices are not unitary.
- FIG. 1 an example embodiment of a Multi-Input, Multi-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) communication system 6 of the present invention is shown.
- the communication system 6 in this example embodiment may be implemented as a wireless system for the transmission and reception of data across a wireless channel 19 .
- the communication system 6 may be part of a wireless Local Area Network (LAN) system or wireless Metropolitan Area Network (MAN) system, cellular telephone system, or other type of radio or microwave frequency system incorporating either one-way or two-way communication over a range of distances.
- the communication system 6 may transmit in a range from 2 to 11 GHz, for example, such as in the unlicensed 5.8 GHz band using a bandwidth of about 3-6 MHz.
- the present invention is also possible for the present invention to be used in a system that comprises an array of sub-channel communication links that carry a number of signals transmitted by a number of transmitting elements to each of a number of receiving elements.
- communication links such as wires in a wiring harness or some alternative wired transmission system, for example, could be used over the distance between a data source and a receiver.
- a transmitter 8 transmits signals across the wireless channel 19 and a receiver 10 receives the transmitted signals.
- the transmitter 8 comprises a data source 12 , which provides the original binary data to be transmitted from the transmitter 8 .
- the data source 12 may provide any type of data, such as, for example, voice, video, audio, text, etc.
- the data source 12 applies the data to an encoder 14 , which encodes the data to allow for error correction.
- the encoder 14 further processes the data so that certain criterion for space-time processing and OFDM are satisfied.
- the encoder 14 separates the data onto multiple paths in the transmitter 8 , each of which will hereinafter be referred to as a transmit diversity branch (TDB).
- TDB transmit diversity branch
- the separate TDBs are input into OFDM modulators 16 , each of which modulates the signal on the respective TDB for transmission by the transmitting antennas 18 .
- the present invention may be used in a Single-Input, Single-Output (SISO) system, which may be considered as a special case of MIMO wherein the number of transmitting and receiving antennas is one.
- SISO Single-Input, Single-Output
- separation of the data by the encoder 14 is not necessary since only one OFDM modulator 16 and antenna 18 is used.
- each frame along each TDB is output from a respective OFDM modulator 16 .
- any number of OFDM modulators 16 may be used.
- the number of OFDM modulators 16 and respective transmitting antennas 18 may be represented by a variable “Q.”
- the OFDM modulators 16 modulate the respective frames at specific sub-carrier frequencies and respective transmitting antennas 18 transmit the modulated frames over the channel 19 .
- a number “L” of receiving antennas 20 receives the transmitted signals, which are demodulated by a number L of respective OFDM demodulators 22 .
- the number L may represent any number and is not necessarily the same as the number Q.
- the number Q of transmitting antennas 18 may be different from the number L of receiving antennas 20 , or they may alternatively be the same.
- the outputs of the demodulators 22 are input into a decoder 24 , which combines and decodes the demodulated signals.
- the decoder 24 outputs the original data, which may be received by a device (not shown) that uses the data.
- the communication system 6 may comprise one or more processors, configured as hardware devices for executing software, particularly software stored in computer-readable memory.
- the processor can be any custom made or commercially available processor, a central processing unit (CPU), an auxiliary processor among several processors associated with a computer, a semiconductor based microprocessor (in the form of a microchip or chip set), a macroprocessor, or generally any device for executing software instructions.
- Suitable commercially available microprocessors are as follows: a PA-RISC series microprocessor from Hewlett-Packard Company, an 80x86 or Pentium series microprocessor from Intel Corporation, a PowerPC microprocessor from IBM, a Sparc microprocessor from Sun Microsystems, Inc, a 68xxx series microprocessor from Motorola Corporation, or a 67xxx series Digital Signal Processor from the Texas Instruments Corporation.
- the communication system 6 can be stored on any computer-readable medium for use by or in connection with any computer-related system or method.
- a computer-readable medium is an electronic, magnetic, optical, or other physical device or means that can contain or store a computer program for use by or in connection with a computer related system or method.
- the communication system 6 can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions.
- a “computer-readable medium” can be any means that can store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.
- the computer-readable medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium. Examples of the computer-readable medium include the following: an electrical connection having one or more wires, a portable computer diskette, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM, EEPROM, or Flash memory), an optical fiber, and a portable compact disc read-only memory (CDROM).
- the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.
- the communication system 6 can be implemented with any or a combination of the following technologies, which are each well known in the art: one or more discrete logic circuits having logic gates for implementing logic functions upon data signals, an application specific integrated circuit (ASIC) having an appropriate combination of logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.
- ASIC application specific integrated circuit
- PGA programmable gate array
- FPGA field programmable gate array
- FIG. 2 shows details of an example embodiment of the encoder 14 shown in FIG. 1.
- the encoder 14 may be configured such that data from the data source 12 is encoded by a channel encoder 26 , which adds parity to the original data to produce channel encoded data.
- the channel encoder 26 encodes the data using a scheme that is recognized by the decoder 24 of the receiver 10 and enables the decoder 24 to detect errors in the received data. Errors may arise as a result of environmental conditions of the channel 19 or noise inadvertently added by the transmitter 8 or receiver 10 .
- the encoder 14 further includes a symbol mapper 28 , which maps the channel-encoded data into data symbols.
- the symbol mapper 28 groups a predetermined number of bits such that each group of bits constitutes a specific symbol chosen from a pre-determined alphabet.
- the symbol mapper 28 further lays out a stream of data symbols within the structure of a frame.
- the encoder 14 further includes a space-time processor 30 that processes the data symbol stream received from the symbol mapper 28 and outputs the processed data symbols via the respective TDBs.
- the space-time processor 30 encodes the data symbol stream in a manner such that the receiver 10 is capable of decoding the signals.
- the data symbols in the TDBs are distributed over Q lines that will eventually be transmitted at precise frequencies spaced apart from each other by a predetermined difference in frequency. By providing a specific frequency difference between the multiple sub-channels, orthogonality can be maintained, thereby preventing the OFDM demodulators 22 from picking up frequencies other than their own designated frequency.
- Each TDB provides an input to a respective adder 34 .
- the other input into each of the adders 34 is connected to the output of a pilot/training symbol inserter 32 , which provides pilot symbols and training symbols to be inserted into the frames on the TDBs.
- Symbols inserted periodically within the data symbols will be referred to herein as “pilot symbols.” These periodic pilot symbols may be inserted anywhere in the stream of the data symbols. If a continuous burst of symbols is inserted by the pilot/training symbol inserter 32 , this type of symbol will be referred to herein as “training symbols” which constitute the preamble.
- the training symbols preferably are inserted at the beginning of the frame. However, the training symbols may be inserted onto the frame in a location other than at the beginning of the frame, such as at the end or in the middle of the frame.
- the pilot/training symbol inserter 32 may be configured so that it is capable of storing multiple sets of training symbols or pilot symbols. In this case, a particular set may be selected, for example, based on desirable communication criteria established by a user.
- the training symbols for each respective sub-channel may preferably be unique to the particular sub-channel. In order to accommodate amplitude differences between the sub-channels, the training symbols may be designed and adjusted to maintain a constant amplitude at the output of each sub-channel.
- Training symbols are preferably transmitted once for every frame. Training symbols are used for periodic calibration (synchronization and channel parameter estimation) whereas pilot symbols are used for minor adjustments to deal with the time-varying nature of the channel.
- the training symbols may be indicative of calibration values or known data values. These calibration values or known values may be transmitted across the channel, and used to calibrate the communication system 6 . Any necessary refinements may be made to the communication system 6 if the received calibration values do not meet desirable specifications.
- the training symbols may be used as specific types of calibration values for calibrating particular channel parameters. By initially estimating these channel parameters, offsets in the time domain and frequency domain may be accounted for so as to calibrate the communication system 6 .
- the training sequence may or may not bypass an Inverse Discrete Fourier Transform (IDFT) stage 38 , which is a part of the embodiment of the OFDM modulator 16 of FIG. 3.
- a training sequence that bypasses the IDFT stage 38 and is directly input into a digital to analog converter (DAC) 44 is referred to herein as a directly modulatable training sequence. Examples of such training sequences may be “chirp-like” sequences. These sequences cover each portion of the bandwidth used by the communication system 6 . Hence, channel response can be easily determined.
- j is given by ⁇ square root ⁇ square root over ( ⁇ 1) ⁇ and is used to denote the quadrature component of the signal.
- s n refers to a time domain signal on the side of the transmitter 8 .
- Frequency domain signals on the transmitter side will hereinafter be referenced by capital letters S k .
- Time and frequency domain signals on the receiver side will hereinafter be written as r n and R k , respectively.
- Other modifications of the chirp-like sequence may be Frank-Zadoff sequences, Chu sequences, Milewski sequences, Suehiro polyphase sequences, and sequences given by Ng et al.
- a training sequence may be generated by modulating each of the symbols on the TDBs with a known sequence of symbols in the frequency domain and passing the symbols through the IDFT stage 38 .
- a known sequence of symbols is obtained from an alphabet which has its constituents on the unit circle in the complex domain and such that the resultant sequence in the time domain has a suitable Peak to Average Power Ratio (PAPR).
- PAPR Peak to Average Power Ratio
- alphabet in communication systems is defined as a finite set of complex values that each of the symbols can assume. For example, an alphabet of a binary phase shift keying (BPSK) system consists of values +1 and ⁇ 1 only.
- An alphabet for a quaternary phase shift keying (QPSK) system consists of the values 1+j, ⁇ 1+j, 1 ⁇ j, and ⁇ 1 ⁇ j.
- the training sequence may be generated by modulating each of the tones of the OFDM block using a BPSK alphabet, which consists of symbols +1 and ⁇ 1.
- the synchronization scheme may be very general such that any known sequence having suitable properties, such as low PAPR, may be used to form the training sequence.
- the adders 34 add the training symbols and pilot symbols to the frame.
- Other embodiments may be used in place of the adders 34 for combining the training symbols and pilot symbols with the data symbols in the frame.
- the adders 34 may include additional inputs to allow for flexibility when adding the pilot/training symbols or in the combining of multiple training symbols or even selectable training symbols. After the training symbols are inserted into frames on the respective TDBs, the frames are output from the encoder 14 and input in respective OFDM modulators 16 .
- FIG. 3 shows an example embodiment of an OFDM modulator 16 , which receives signals along one of the TDBs.
- the number of OFDM modulators 16 is preferably equal to the number of transmitting antennas 18 .
- SISO systems there is only one OFDM modulator 16 and one transmitting antenna 18 .
- MIMO systems there may be any number of OFDM modulators 16 and transmitting antennas 18 .
- the respective signal from the encoder 14 is input into a serial-to-parallel converter 36 of the OFDM modulator 16 .
- the serial-to-parallel converter 36 takes N symbols received in a serial format and converts them into a parallel format.
- the variable N will be referred to herein as the blocksize of the OFDM symbol.
- the N parallel symbols are processed by an Inverse Discrete Fourier Transform (IDFT) stage 38 , which transforms the frequency signals to the time domain.
- IFT Inverse Discrete Fourier Transform
- a method is proposed herein to design the training symbols such that the transforms of all the sequences from the IDFT stage 38 will have a constant magnitude.
- PAPR peak to average power ratio
- the output from the IDFT stage 38 is input into a cyclic prefix inserter 40 , which inserts an additional number of samples for every N samples.
- the number of samples inserted by the cyclic prefix inserter 40 will be referred to herein by the variable “G.”
- the G samples are intended to be inserted as guard intervals to separate the N adjacent data symbols from each other in time by a separation adequate to substantially eliminate Inter Symbol Interference (ISI).
- the cyclic prefix inserter 40 repeats G samples from a latter portion of the N samples output from the IDFT stage 38 and inserts the G samples as a prefix to each of the data samples.
- the time length of the cyclic prefix is greater than the maximum time delay of a transmitted signal across the channel 19 .
- the nature of the channel 19 may be susceptible to a variation in the delay time from the transmitted antennas 18 to the receiving antennas 20 , it may be desirable to increase, or even double, the length of cyclic prefixes of the preamble to ensure that the time delay of the channel does not exceed the time of the cyclic prefix, thereby eliminating ISI.
- the G+N samples herein referred to as an OFDM symbol, are then converted from a parallel format to a serial format using parallel-to-serial converter 42 , and then inputted to a digital-to-analog converter (DAC) 44 for conversion into analog signals.
- the output from the DAC 44 is input into a mixer 48 .
- a local oscillator 46 provides a signal having the carrier frequency to the other input of the mixer 48 to up-convert the respective OFDM symbol from baseband to RF.
- the frame is amplified by an amplifier 50 .
- an amplifier 50 may be backed off to prevent it from going into its non-linear region.
- the present invention may provide certain specific sequences that can be used in order to make the PAPR minimal or unity.
- Each OFDM modulator 16 preferably comprises the same components as the OFDM modulator 16 shown in FIG. 3. Other techniques for designing the OFDM modulators 16 may be used in order to transmit the multiple frames across the channel 19 with minimal interference.
- Each frame output from the respective OFDM modulator 16 is transmitted by a respective antenna 18 .
- the antennas 18 may be spaced apart from each other by any desirable separation. For example, the separation distance may be in a range from a few millimeters to several meters.
- FIG. 4 illustrates an example of a frame 52 that is transmitted across the channel 19 from the transmitting antennas 18 to the receiving antennas 20 .
- the frame 52 comprises a preamble 54 comprising a number of training symbols N I and cyclic prefixes G.
- the preamble 54 is inserted by the pilot/training symbol inserter 32 as mentioned above.
- the data frame 52 comprises a data portion 56 consisting of a plurality of OFDM data symbols N and cyclic prefixes G, which are inserted before each of the OFDM data symbols N.
- the pilot/training symbol inserter 32 further inserts pilot symbols (not shown) intermittently within the OFDM data symbols N.
- the task of the preamble 54 and training symbols N I in the frame is to help the receiver 10 identify the arrival of the frame 52 and hence perform time synchronization, frequency synchronization, and channel parameter estimation.
- the preamble 54 in general, consists of Q or more training symbols, wherein each training symbol has a length of G+N I samples in time.
- N I may be 1 ⁇ 4 N. If no predetermined N I has been established, the variable N I may be given the value equal to N.
- the training symbol length may be shorter than the length of the symbols in the data portion 56 , which has a length of G+N samples.
- FIG. 5 shows a portion of the MIMO OFDM communication system 6 of FIG. 1 along with details of a signal transmission matrix S and a received demodulated OFDM sample matrix R.
- the signals of the communication system 6 can be expressed using the equation:
- R k,T ⁇ L S k,T ⁇ Q ⁇ k,Q ⁇ L +W k,T ⁇ L
- R is a T ⁇ L received demodulated OFDM sample matrix
- ⁇ is a Q ⁇ L matrix of channel coefficients that are indicative of the characteristics of the channel across which the signals are transmitted
- S is a T ⁇ Q signal transmission matrix
- W is a T ⁇ L noise matrix that corrupts and distorts the received sample matrix R.
- T may or may not be equal to Q. However, for simplicity, T is assumed to be equal to Q herein.
- the signal transmission matrix S shown in FIG. 5 consists of Q OFDM symbols that are simultaneously transmitted from Q transmit antennas 18 over Q or more OFDM symbol periods (T s ). For example, at a first time instance t, the OFDM symbols S 1 , S 2 , . . . S Q are transmitted from the first to the Qth antennas 18 . At a second time instance t+T S , the OFDM symbols S Q+1 , S Q+2 , . . . S 2Q are transmitted from the same antennas 18 . The OFDM symbol transmissions are repeated at each time instance until all of the OFDM symbols of the matrix S have been transmitted.
- the S matrix consists of Q or more training symbols, each of which is less than or equal to the length of an OFDM symbol in the time dimension.
- the training symbols are simultaneously transmitted from the transmitting antennas 18 as represented by equations (1) and (2), wherein the different antennas correspond to the space dimension.
- the S matrix consists of Q or more data symbols each occupying an OFDM symbol in the time dimension.
- the pilot/training symbol inserter 32 inserts the pilot symbols within the data symbols.
- the data symbols are encoded, modulated, and transmitted from the transmitting antennas 18 .
- Each signal transmission matrix S of Q ⁇ Q OFDM symbols are transmitted over the communication channel 19 , which naturally comprises a matrix of channel coefficients ⁇ .
- the communication channel 19 further includes characteristics that distort and degrade the transmitted signal, thereby adding a noise matrix W, before the signal transmission matrix S is received at the L receive antennas 20 .
- FIG. 5 further illustrates how each of the L receiving antennas 20 receives each of the Q transmitted signals.
- the first receive antenna 20 receives OFDM signals over channel impulse responses h 11 , h 21 , h 31 . . . h Q1 from the first to the Qth transmitting antennas 18 , respectively.
- the term h i,j refers to the channel impulse response from the i th transmit to the j th receive antenna in the time domain.
- the last receive antenna 20 receives the transmitted signals over the channel impulse responses h 1L , h 2L , h 3L , . . . h QL from the first to the Qth transmitting antennas 18 , respectively.
- only the signals received at the first and last receiving antennas 20 are shown. However, it should be understood that each receiving antenna 20 receives the signals transmitted from the Q transmitting antennas 18 .
- the received signals are demodulated by the respective OFDM demodulators 22 , which provide the received demodulated OFDM sample matrix R.
- the samples R 1 , R Q+1 , . . . R (L ⁇ 1)Q+1 are received.
- the samples R 2 , R Q+2 . . . R (L ⁇ 1)Q+2 are received.
- the samples are received at each time instance until all of the samples in the received demodulated OFDM sample matrix R are received. It should be noted that the time instances used for the matrices S and R are given the same variable, but, in essence, a delay occurs as is well known in the art.
- a significant task of the receiver 10 is to estimate the time of arrival of the transmitted signal. This process is called “time synchronization.”
- time synchronization In addition to time synchronization, OFDM systems typically require frequency synchronization as well. Because there usually exists a certain difference between the local oscillator frequencies of the transmitter and the receiver, the received signals experience a loss of sub-carrier orthogonality, which should typically be corrected in order to avoid degradation in system performance.
- FIG. 6 shows a detailed illustration of the received demodulated OFDM sample matrix R which consists of L columns and Q or more rows of OFDM symbols with respect to space and time, respectively.
- the matrix R consists of three dimensions, namely space, time and frequency.
- the frequency axis indicates the amplitude of the frequency component received at each receiving antenna 20 from each transmitting antenna 18 .
- Each of the matrices R and ⁇ can be seen to consist of either N matrices of dimension Q ⁇ L or Q ⁇ L vectors of length N.
- the training symbol length may be equal to the data symbol length.
- the length of the training symbol in the preamble may be (N+G) since it is possible to estimate the characteristics of the channel even if the training symbol length is shortened to N I +G such that (N 1 +G) ⁇ (N+G).
- Transmission of the training sequence of length N I corresponds to exciting every Ith sub-channel of an OFDM signal having a block size N. This means that no information is transmitted on the remaining (1 ⁇ 1/I)N sub-channels and the estimates of the channel for the sub-channels are derived from the ones that actually include information.
- the training sequence of length N I may be generated by first modulating every Ith sub-channel of the OFDM block by a known sequence of symbols and zero padding the rest. An N-point IDFT is taken to obtain N samples in the time domain, and finally only the first N I samples along with its cyclic prefix are transmitted. At the receiver after synchronization, the samples corresponding to the training sequence of length N I are repeated I times before being demodulated by the OFDM demodulators.
- many more sub-channels are zero padded to reduce the interference between the adjacent bands and to facilitate the system implementation. For example, in the systems based on the IEEE 802.16a/b standard, a total of 56 tones or sub-carriers are zero padded.
- the training sequence structure in the frequency domain is represented by its signal transmission matrix, which is configured in such a way so as to have certain properties that aid in synchronization and channel estimation.
- the rows of the signal transmission matrix represent the time dimension, the columns represent the space dimension and the index k represents the frequency dimension or the corresponding sub-carrier.
- the transmitter 8 may create the matrix S k such that it is unitary. If the vectors of the training sequences are derived from the points along the unit circle in the complex domain then the signal transmission matrices S k shown in (1) and (2) are unitary. Besides making each of the transmission matrices S k unitary, it also facilitates the system implementation and maintains a low PAPR of the sequence structure in the time domain. This is because the signal transmission matrices in the training mode and the data mode are exactly alike, which further simplifies the system implementation. The transmission of a unitary matrix aids in parameter estimation, as is described below.
- the L number of receiving antennas 20 receive the Q number of transmitted signals and provide the received signals to respective OFDM demodulators 22 , which down-convert the signal back to baseband.
- the L number of receiving antennas 20 are separated by a distance such that the received signals have minimum correlation and are as independent from each other as possible.
- the outputs from the L number of OFDM demodulators 22 are input into a decoder 24 , which combines the multiple signals and decodes them.
- the decoder 24 removes any correctable noise and distortion errors, as will be described below, and outputs signals representative of the original data.
- FIG. 7 illustrates an example embodiment of one of the OFDM demodulators 22 of the receiver 10 .
- Received signals from the receiving antenna 20 are input into a pre-amplifier 57 , which amplifies the received signals to a level at which further processing may be performed.
- the output of the pre-amplifier 57 is connected to a mixer 58 .
- a local oscillator 59 provides a signal to the mixer 58 having a frequency designed to demodulate the received amplified signal.
- the demodulated signal is then output to an analog-to-digital converter (ADC) 60 , which converts the analog signals into discrete time samples.
- ADC analog-to-digital converter
- OFDM typically requires substantial synchronization in time as well as in frequency in order that transmitted signals can be recovered with adequate accuracy.
- Time synchronization involves determining the best possible time for the start of the received frame to closely match the start of the transmitted signal.
- Frequency synchronization involves maintaining orthogonality of the respective sub-carrier frequencies.
- Orthogonality refers to a condition of the sub-carrier frequencies wherein the “inner product” of the signals at different sub-carrier frequencies is zero.
- the time domain sequences S 2,n are transmitted.
- ICI Inter Carrier Interference
- the synchronization circuit 61 corrects this loss of sub-channel orthogonality by finding an estimate of the difference between the frequencies of the local oscillators 46 of the transmitter 8 and the frequencies of the local oscillators 59 of the receiver 10 .
- the synchronization circuit 61 further corrects these frequency difference estimates.
- the frequency and time synchronized information is provided to the cyclic prefix remover 62 , which removes the cyclic prefixes inserted between each block of N symbols.
- the blocks of N samples are then serial-to-parallel converted using serial-to-parallel converter 63 and the parallel signals are input to a Discrete Fourier Transform (DFT) stage 64 , which converts the time domain samples back to the frequency domain, thus completing synchronization and demodulation by the OFDM demodulators 22 .
- DFT Discrete Fourier Transform
- the L number of demodulated signals from each of the L number of OFDM demodulators 22 are then input into the decoder 24 , which processes the demodulated signals.
- the decoder 24 may be configured in the manner shown in the example embodiment of FIG. 8.
- the decoder 24 comprises a space-time processor 110 and a parameter estimator 112 . Both the space-time processor 110 and parameter estimator 112 receive the signals from each of the L number of OFDM demodulators 22 .
- An output from the parameter estimator 112 is input into a symbol demapper 116 and a set of outputs is input into the space-time processor 110 .
- the output of the space-time processor 110 is converted from parallel to serial by a parallel-to-serial converter 114 and then input to the symbol demapper 116 , which maps the symbols from the predetermined alphabet back to the data bits.
- the output from the symbol demapper 116 is input into a channel decoder 118 .
- the channel decoder 118 decodes the data symbols by checking the parity that was added to the symbols prior to transmission. Thus, the channel decoder 118 detects and corrects errors in the data symbols and outputs the data in its original form.
- the parameter estimator 112 estimates characteristics of the channel across which the communication signals are transmitted. These channel characteristics or parameters may include, for example, the channel coefficient matrix ⁇ , signal to noise ratio (SNR), noise variance, time correlation, and frequency correlation. Having knowledge of the unique channel parameters enables the receiver 10 to compensate for the various distortions introduced by the channel. Since the receiver 10 does not have prior knowledge of the channel parameters, the parameter estimator 112 calculates an estimation of the channel parameters, based on the training sequence transmitted by the transmitter 8 .
- SNR signal to noise ratio
- the received OFDM samples belonging to the training symbols of length N I , and a copy of the transmitted training sequences of length N I are repeated I times and their N-point FFT are taken to convert the received OFDM sample matrix R and the OFDM signal transmission matrix S to have their dimension in the frequency domain to be N.
- FIG. 9 shows a first embodiment of a method performed by the parameter estimator 112 for calculating channel estimates.
- the parameter estimator 112 derives its estimates using a Least Squares (LS) method. If a certain number T of training symbols are transmitted from all the Q transmit antennas, where T ⁇ Q, then the LS estimates are obtained as
- the signal transmission matrix S for each of the sub-carriers has T rows and Q columns.
- the channel estimates so obtained minimize the error between the estimated channel coefficient matrix and the actual channel coefficient matrix for each tone. It should be noted that the N I channel coefficient matrices so obtained are only representative of those tones that were excited in the transmitted sequence. The channel coefficient matrix for all the other tones are set to zero.
- the parameter estimator 112 provides the exact estimates of the channel coefficient matrices. This type of parameter estimator is called a zero-forcing estimator. Also, by using the LS method, the hardware complexity is reduced considerably since the same circuitry can be used for the data symbols as well as the training symbols.
- the transmitter 8 creates the transmitting matrices S such that the matrices are unitary as described above, then the preamble may be formed having only Q symbols.
- the training symbols may be created having fewer than Q symbols, and may even be created having one symbol.
- the method of FIG. 9 comprises a first step (block 120 ) for calculating coarse channel estimates of the channel coefficient matrix using an LS method and/or a Zero forcing method, if the S k s are unitary.
- the coarse channel estimates may be calculated by a formula such as:
- An aim of the channel estimation algorithm is to estimate the channel coefficients for all the sub-carriers.
- N I is not equal to N
- the channel coefficients are available for only N I sub-carriers since the received OFDM training symbol of length N I was repeated I times before passing through the DFT stage 64 .
- a frequency domain interpolation procedure is performed, as indicated by block 124 .
- a simple linear interpolation scheme may be used to estimate the unexcited sub-carriers.
- MSE mean square error
- a step of reducing the mean square error (block 126 ). Since the MSE of the channel estimates of the LS estimator is typically high, it is usually desirable to reduce the MSE.
- ⁇ e 2 ⁇ j/N .
- the reduction of the MSE by the previous steps provides accurate estimates of the channel parameters.
- the parameter estimator 112 outputs these fine channel estimates to the space-time processor 110 in order to compensate for the unique channel parameters.
- Other than the method mentioned above to reduce the MSE in LS channel estimates one can follow a number of different methods for reducing MSE, such as performing a smoothing procedure in the frequency domain, a Linear Prediction (LP) procedure, a method where decisions are fed back to the parameter estimator, a decision directed update procedure, etc.
- LP Linear Prediction
- FIG. 10 Alternative to the embodiment of FIG. 9, another embodiment for calculating fine channel estimates is illustrated in FIG. 10.
- This embodiment refers to the case mentioned earlier when a large number of sub-carriers of the OFDM symbols are zero padded to facilitate the system implementation.
- the signal transmission matrix S may or may not be unitary and the training sequence includes Q training symbols.
- a first step includes zero padding the recommended sub-carriers in the training sequence. For example, in a system that meets the IEEE 802.16a/b standard, sub-carriers at DC and 55 others at high frequencies are set to zero. This sub-carrier elimination step simplifies the system implementation and further avoids adjacent channel interference.
- the above-mentioned method of MSE reduction typically cannot be applied directly since the channel estimates are not available for the zero-padded sub-carriers.
- the sub-carrier frequencies that are eliminated may be initially estimated using frequency domain extrapolation on the existing LS estimates.
- the channel estimates at DC can be calculated by taking an average of the channel estimates for the positive and negative frequencies.
- the estimates of the eliminated sub-carrier frequencies are used to reduce the MSE in the channel estimates but are otherwise ignored since no data is transmitted on these sub-carriers.
- Block 136 includes the step of performing interpolating in the frequency domain. This step is identical to step 124 of FIG. 9.
- the method of FIG. 10 proceeds to block 138 where a frequency domain extrapolation takes place. Frequencies at the low and high ends are extrapolated based on the existing middle frequencies in order to arrive at the estimates for these frequencies.
- step 140 is the same as step 126 of FIG. 9. Since only the MSE-reduced estimates of a selected range of transmitted sub-carrier frequencies are used, the unused frequencies outside the transmission bandwidth are discarded, as indicated in block 142 . Thus, the fine estimates of the channel parameters having been obtained at the end of block 142 , the parameter estimator 112 outputs the fine channel estimates to the space-time processor 110 .
- the parameter estimator 112 may further calculate estimates of the “noise variance,” which is a parameter representing the power of the extraneous unwanted noise present in the signal.
- the noise variance is based on the coarse channel estimates and can be obtained for each of the receiving antennas 20 .
- FIG. 11 shows an embodiment of a noise variance estimation method.
- Block 150 indicates a step wherein noise variance estimates for each of the receive antennas can be calculated.
- g ij,n is the coefficient of the time domain coarse channel estimates for the i th transmit and j th receive antennas obtained from the parameter estimator 112 .
- the noise variance is calculated for each of the j receive antennas.
- noise variance estimation is a little more complex.
- This alternative noise variance estimation method is shown in FIG. 12.
- a noise term is determined by subtracting the matrices of the fine channel estimates from the matrices of the coarse channel estimates, whereby the coarse channel estimates and fine channel estimates are obtained from the parameter estimator 112 as described above with reference to the channel estimation methods of FIGS. 9 and 10.
- Calculation of the noise terms is shown using block 152 and can be represented using the following equation:
- the next step includes multiplying the matrices G k ′ with the signal transmission matrices S k as is represented by block 154 and as is given by the following equation:
- the next step is to convert the frequency domain coefficients to the time domain, which is represented using block 156 and can be described using the following equation.
- the parameter estimator 112 may include software stored in memory, wherein the software may include one or more separate programs, each of which comprises an ordered listing of executable instructions for implementing logical functions.
- the software may include the parameter estimator system in accordance with the present invention and a suitable operating system (O/S).
- Suitable commercially available operating systems are as follows: a Windows operating system available from Microsoft Corporation; a Netware operating system available from Novell, Inc.; a Macintosh operating system available from Apple Computer, Inc.; a UNIX operating system available from the Hewlett-Packard Company, Sun Microsystems, Inc., or AT&T Corporation; a LINUX freeware operating system that is readily available on the Internet; a run time Vxworks operating system available from WindRiver Systems, Inc.; an appliance-based operating system, such as that implemented in a handheld computer or personal data assistant (PDA) (e.g., PalmOS available from Palm Computing, Inc. or Windows CE available from Microsoft Corporation).
- PDA personal data assistant
- the O/S essentially controls the execution of other computer programs, such as the parameter estimation system, and provides scheduling, input-output control, file and data management, memory management, and communication control and related services.
- the parameter estimator 112 can be implemented in hardware, software, firmware, or a combination thereof.
- the parameter estimator 112 can be implemented in software or firmware that is stored in a memory and that is executed by a suitable instruction execution system.
- the synchronization system can be implemented with any or a combination of the following technologies, which are all well known in the art: a discrete logic circuit having logic gates for implementing logic functions upon data signals, an application specific integrated circuit (ASIC) having appropriate combinational logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), digital signal processor (DSP), etc.
Abstract
Description
- This application claims priority to copending U.S. provisional application entitled “Parameter Estimation for MIMO OFDM Systems,” having Ser. No. 60/286,130, filed on Apr. 24, 2001, which is entirely incorporated herein by reference.
- This application is related to copending U.S. provisional application entitled, “Synchronization for MIMO OFDM Systems,” having Ser. No. 60/286,180, filed Apr. 24, 2001, which is entirely incorporated herein by reference.
- The present invention is generally related to wireless communication systems that employ Orthogonal Frequency Division Multiplexing (OFDM). More particularly, the present invention is related to an apparatus and method for estimating channel parameters in a Multi-Input, Multi-Output (MIMO) OFDM system.
- In wireless communication systems, recent developments have been made using technologies wherein multiple signals are simultaneously transmitted over a single transmission path. In Frequency Division Multiplexing (FDM), the frequency spectrum is divided into sub-channels. Information (e.g. voice, video, audio, text, etc.) is modulated and transmitted over these sub-channels at different sub-carrier frequencies.
- In Orthogonal Frequency Division Multiplexing (OFDM) schemes, the sub-carrier frequencies are spaced apart by precise frequency differences. Because of the ability of OFDM systems to overcome the multiple path effects of the channel, and to transmit and receive large amounts of information, much research has been performed to advance this technology. By using multiple transmitting antennas and multiple receiving antennas in OFDM systems, it is possible to increase the capacity of transmitted and received data while generally using the same amount of bandwidth as in a system with one transmit and one receive antenna.
- OFDM technologies are typically divided into two categories. The first category is the Single-Input, Single-Output (SISO) scheme, which utilizes a single transmitting antenna to transmit radio frequency (RF) signals and a single receiving antenna to receive the RF signals. The second category is the Multi-Input, Multi-Output (MIMO) scheme, which uses multiple transmitting antennas and multiple receiving antennas.
- In typical communication systems, training symbols, or preamble, at the beginning of data frames, are usually added as a prefix to the data symbols. The data symbols, of course, include the useful data or information (e.g., voice, data, video, etc.), which is meant to be transmitted to a remote location. The training symbols in SISO systems are used to provide synchronization of the received signals with respect to the transmitted signals, as well as to provide channel parameter estimation.
- Although training symbols used for SISO systems can be used to provide synchronization in a MIMO system, the training symbols cannot provide for channel parameter estimation in the MIMO system. In fact, no method or apparatus exists for MIMO systems that is capable of providing time and frequency synchronization as well as channel parameter estimation. Thus, a need exists for a method and apparatus that is capable of providing time and frequency synchronization in MIMO systems and can further perform channel estimation.
- The present invention provides systems and methods that overcome the deficiencies of the prior art as mentioned above. The present invention utilizes a sequence of training symbols or preambles that may be used in both Single-Input, Single-Output (SISO) and Multi-Input, Multi-Output (MIMO) systems, using any number of transmitting and receiving antennas. An embodiment of the present invention comprises an apparatus that can be used to estimate channel parameters across which a data frame is transmitted in a MIMO system. In conjunction with a synchronization scheme, the parameter estimator calculates an accurate estimation of the characteristics of the channel, thereby making the MIMO systems operational. The present invention achieves an accurate estimation of channel parameters and further achieves synchronization in the time domain and frequency domain and, therefore, enables MIMO systems to operate acceptably.
- One MIMO Orthogonal Frequency Division Multiplexing (OFDM) system of the present invention includes a number of OFDM modulators, which provide data frames to be transmitted across a channel. The data frames of the present invention comprise one or more training symbols, a plurality of data symbols, and cyclic prefixes inserted between the data symbols. A number of transmitting antennas corresponding to the number of modulators are used to transmit the modulated signals over the channel. A number of receiving antennas are used to receive the transmitted signals. The received signals are demodulated by a number of OFDM demodulators corresponding to the number of receiving antennas and decoded by an OFDM decoder, which processes the data frames. By utilizing the structure embedded in the training symbols, the MIMO system of the present invention is capable of providing time and frequency synchronization as well as perform channel estimation.
- A method of the present invention is also provided, wherein parameter estimation is carried out in a MIMO system. The method includes producing data frames comprising at least one training symbol, multiple data symbols and cyclic prefixes. The data frames are transmitted over the channel, received, demodulated, and processed. By processing the training symbol of the data frame, an estimation of the parameters of the channel may be achieved from the data frame.
- Other systems, methods, features, and advantages of the present invention will become apparent to a person having skill in the art upon examination of the following drawings and detailed description. All such additional systems, methods, features, and advantages are within the scope of the present invention.
- Many aspects of the invention can be better understood with reference to the following drawings. Moreover, in the drawings, like reference numerals designate corresponding parts throughout the several views.
- FIG. 1 is a block diagram illustrating an example embodiment of a Multi-Input, Multi-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) system.
- FIG. 2 is a block diagram illustrating an example embodiment of the MIMO encoder shown in FIG. 1.
- FIG. 3 is a block diagram illustrating an example embodiment of one of the OFDM modulators shown in FIG. 1.
- FIG. 4 illustrates an example frame structure for a MIMO OFDM system.
- FIG. 5 is a block diagram illustrating an example matrix of a transmitted sequence structure and an example matrix of a received sequence structure using the modulator/demodulator arrangement shown in FIG. 1.
- FIG. 6 illustrates a three-dimensional representation of the received sequence structure in detail.
- FIG. 7 is a block diagram illustrating an example embodiment of one of the OFDM demodulators shown in FIG. 1.
- FIG. 8 is a block diagram illustrating an example embodiment of the decoder shown in FIG. 1.
- FIG. 9 is a flow chart of a first embodiment of a method for calculating fine channel estimates.
- FIG. 10 is a flow chart of a second embodiment of a method for calculating fine channel estimates.
- FIG. 11 is a flow chart of an example embodiment of a method for calculating noise variance estimates when the signal transmission matrices are unitary.
- FIG. 12 is a flow chart of an example embodiment of a method for calculating noise variance estimates when the signal transmission matrices are not unitary.
- In FIG. 1, an example embodiment of a Multi-Input, Multi-Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM)
communication system 6 of the present invention is shown. Thecommunication system 6 in this example embodiment may be implemented as a wireless system for the transmission and reception of data across awireless channel 19. Thecommunication system 6, for example, may be part of a wireless Local Area Network (LAN) system or wireless Metropolitan Area Network (MAN) system, cellular telephone system, or other type of radio or microwave frequency system incorporating either one-way or two-way communication over a range of distances. Thecommunication system 6 may transmit in a range from 2 to 11 GHz, for example, such as in the unlicensed 5.8 GHz band using a bandwidth of about 3-6 MHz. - It is also possible for the present invention to be used in a system that comprises an array of sub-channel communication links that carry a number of signals transmitted by a number of transmitting elements to each of a number of receiving elements. In this latter case, communication links, such as wires in a wiring harness or some alternative wired transmission system, for example, could be used over the distance between a data source and a receiver.
- In the example embodiment of FIG. 1, a
transmitter 8 transmits signals across thewireless channel 19 and areceiver 10 receives the transmitted signals. Thetransmitter 8 comprises adata source 12, which provides the original binary data to be transmitted from thetransmitter 8. Thedata source 12 may provide any type of data, such as, for example, voice, video, audio, text, etc. Thedata source 12 applies the data to anencoder 14, which encodes the data to allow for error correction. Theencoder 14 further processes the data so that certain criterion for space-time processing and OFDM are satisfied. Theencoder 14 separates the data onto multiple paths in thetransmitter 8, each of which will hereinafter be referred to as a transmit diversity branch (TDB). The separate TDBs are input intoOFDM modulators 16, each of which modulates the signal on the respective TDB for transmission by the transmittingantennas 18. The present invention may be used in a Single-Input, Single-Output (SISO) system, which may be considered as a special case of MIMO wherein the number of transmitting and receiving antennas is one. In the SISO system example, separation of the data by theencoder 14 is not necessary since only oneOFDM modulator 16 andantenna 18 is used. - During the encoding by the
encoder 14 and modulating by theOFDM modulators 16, data is normally bundled into groups such that the collection of each group of data is referred to as a “frame.” Details of the frame as used in the present invention will be described in more detail below with reference to FIG. 4. Each frame along each TDB is output from arespective OFDM modulator 16. As illustrated in FIG. 1, any number ofOFDM modulators 16 may be used. The number ofOFDM modulators 16 andrespective transmitting antennas 18 may be represented by a variable “Q.” The OFDM modulators 16 modulate the respective frames at specific sub-carrier frequencies andrespective transmitting antennas 18 transmit the modulated frames over thechannel 19. - On the side of the
receiver 10, a number “L” of receivingantennas 20 receives the transmitted signals, which are demodulated by a number L ofrespective OFDM demodulators 22. The number L may represent any number and is not necessarily the same as the number Q. In other words, the number Q of transmittingantennas 18 may be different from the number L of receivingantennas 20, or they may alternatively be the same. The outputs of thedemodulators 22 are input into adecoder 24, which combines and decodes the demodulated signals. Thedecoder 24 outputs the original data, which may be received by a device (not shown) that uses the data. - The
communication system 6 may comprise one or more processors, configured as hardware devices for executing software, particularly software stored in computer-readable memory. The processor can be any custom made or commercially available processor, a central processing unit (CPU), an auxiliary processor among several processors associated with a computer, a semiconductor based microprocessor (in the form of a microchip or chip set), a macroprocessor, or generally any device for executing software instructions. Examples of suitable commercially available microprocessors are as follows: a PA-RISC series microprocessor from Hewlett-Packard Company, an 80x86 or Pentium series microprocessor from Intel Corporation, a PowerPC microprocessor from IBM, a Sparc microprocessor from Sun Microsystems, Inc, a 68xxx series microprocessor from Motorola Corporation, or a 67xxx series Digital Signal Processor from the Texas Instruments Corporation. - When the
communication system 6 is implemented in software, it should be noted that thecommunication system 6 can be stored on any computer-readable medium for use by or in connection with any computer-related system or method. In the context of this document, a computer-readable medium is an electronic, magnetic, optical, or other physical device or means that can contain or store a computer program for use by or in connection with a computer related system or method. Thecommunication system 6 can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. In the context of this document, a “computer-readable medium” can be any means that can store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device. The computer-readable medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, device, or propagation medium. Examples of the computer-readable medium include the following: an electrical connection having one or more wires, a portable computer diskette, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM, EEPROM, or Flash memory), an optical fiber, and a portable compact disc read-only memory (CDROM). Note that the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory. - In an alternative embodiment, where the
communication system 6 is implemented in hardware, the communication system can be implemented with any or a combination of the following technologies, which are each well known in the art: one or more discrete logic circuits having logic gates for implementing logic functions upon data signals, an application specific integrated circuit (ASIC) having an appropriate combination of logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), etc. - The
encoder 14 andOFDM modulators 16 of thetransmitter 8 will now be described with respect to FIGS. 2 and 3. FIG. 2 shows details of an example embodiment of theencoder 14 shown in FIG. 1. Theencoder 14 may be configured such that data from thedata source 12 is encoded by achannel encoder 26, which adds parity to the original data to produce channel encoded data. Thechannel encoder 26 encodes the data using a scheme that is recognized by thedecoder 24 of thereceiver 10 and enables thedecoder 24 to detect errors in the received data. Errors may arise as a result of environmental conditions of thechannel 19 or noise inadvertently added by thetransmitter 8 orreceiver 10. - The
encoder 14 further includes asymbol mapper 28, which maps the channel-encoded data into data symbols. Thesymbol mapper 28 groups a predetermined number of bits such that each group of bits constitutes a specific symbol chosen from a pre-determined alphabet. Thesymbol mapper 28 further lays out a stream of data symbols within the structure of a frame. - The
encoder 14 further includes a space-time processor 30 that processes the data symbol stream received from thesymbol mapper 28 and outputs the processed data symbols via the respective TDBs. The space-time processor 30 encodes the data symbol stream in a manner such that thereceiver 10 is capable of decoding the signals. The data symbols in the TDBs are distributed over Q lines that will eventually be transmitted at precise frequencies spaced apart from each other by a predetermined difference in frequency. By providing a specific frequency difference between the multiple sub-channels, orthogonality can be maintained, thereby preventing the OFDM demodulators 22 from picking up frequencies other than their own designated frequency. - Each TDB provides an input to a
respective adder 34. The other input into each of theadders 34 is connected to the output of a pilot/training symbol inserter 32, which provides pilot symbols and training symbols to be inserted into the frames on the TDBs. Symbols inserted periodically within the data symbols will be referred to herein as “pilot symbols.” These periodic pilot symbols may be inserted anywhere in the stream of the data symbols. If a continuous burst of symbols is inserted by the pilot/training symbol inserter 32, this type of symbol will be referred to herein as “training symbols” which constitute the preamble. The training symbols preferably are inserted at the beginning of the frame. However, the training symbols may be inserted onto the frame in a location other than at the beginning of the frame, such as at the end or in the middle of the frame. - The pilot/
training symbol inserter 32 may be configured so that it is capable of storing multiple sets of training symbols or pilot symbols. In this case, a particular set may be selected, for example, based on desirable communication criteria established by a user. The training symbols for each respective sub-channel may preferably be unique to the particular sub-channel. In order to accommodate amplitude differences between the sub-channels, the training symbols may be designed and adjusted to maintain a constant amplitude at the output of each sub-channel. - Training symbols are preferably transmitted once for every frame. Training symbols are used for periodic calibration (synchronization and channel parameter estimation) whereas pilot symbols are used for minor adjustments to deal with the time-varying nature of the channel. The training symbols may be indicative of calibration values or known data values. These calibration values or known values may be transmitted across the channel, and used to calibrate the
communication system 6. Any necessary refinements may be made to thecommunication system 6 if the received calibration values do not meet desirable specifications. - Furthermore, the training symbols may be used as specific types of calibration values for calibrating particular channel parameters. By initially estimating these channel parameters, offsets in the time domain and frequency domain may be accounted for so as to calibrate the
communication system 6. The training sequence may or may not bypass an Inverse Discrete Fourier Transform (IDFT) stage 38, which is a part of the embodiment of theOFDM modulator 16 of FIG. 3. A training sequence that bypasses the IDFT stage 38 and is directly input into a digital to analog converter (DAC) 44 is referred to herein as a directly modulatable training sequence. Examples of such training sequences may be “chirp-like” sequences. These sequences cover each portion of the bandwidth used by thecommunication system 6. Hence, channel response can be easily determined. In general, a chirp sequence in the time domain is given by the equation: - where j is given by {square root}{square root over (−1)} and is used to denote the quadrature component of the signal. It should be noted that the term sn refers to a time domain signal on the side of the
transmitter 8. Frequency domain signals on the transmitter side will hereinafter be referenced by capital letters Sk. Time and frequency domain signals on the receiver side will hereinafter be written as rn and Rk, respectively. Other modifications of the chirp-like sequence may be Frank-Zadoff sequences, Chu sequences, Milewski sequences, Suehiro polyphase sequences, and sequences given by Ng et al. By observing the response of thereceiver 10 to the chirp signals, the channel parameters may be estimated. - In the case when the IDFT stage38 is not bypassed, a training sequence may be generated by modulating each of the symbols on the TDBs with a known sequence of symbols in the frequency domain and passing the symbols through the IDFT stage 38. Generally, such a known sequence of symbols is obtained from an alphabet which has its constituents on the unit circle in the complex domain and such that the resultant sequence in the time domain has a suitable Peak to Average Power Ratio (PAPR). The term “alphabet” in communication systems is defined as a finite set of complex values that each of the symbols can assume. For example, an alphabet of a binary phase shift keying (BPSK) system consists of values +1 and −1 only. An alphabet for a quaternary phase shift keying (QPSK) system consists of the
values 1+j, −1+j, 1−j, and −1−j. For example, the training sequence may be generated by modulating each of the tones of the OFDM block using a BPSK alphabet, which consists of symbols +1 and −1. The synchronization scheme may be very general such that any known sequence having suitable properties, such as low PAPR, may be used to form the training sequence. - With reference again to FIG. 2, the
adders 34 add the training symbols and pilot symbols to the frame. Other embodiments may be used in place of theadders 34 for combining the training symbols and pilot symbols with the data symbols in the frame. Furthermore, theadders 34 may include additional inputs to allow for flexibility when adding the pilot/training symbols or in the combining of multiple training symbols or even selectable training symbols. After the training symbols are inserted into frames on the respective TDBs, the frames are output from theencoder 14 and input inrespective OFDM modulators 16. - FIG. 3 shows an example embodiment of an
OFDM modulator 16, which receives signals along one of the TDBs. The number ofOFDM modulators 16 is preferably equal to the number of transmittingantennas 18. In SISO systems, there is only oneOFDM modulator 16 and one transmittingantenna 18. In MIMO systems, there may be any number ofOFDM modulators 16 and transmittingantennas 18. - The respective signal from the
encoder 14 is input into a serial-to-parallel converter 36 of theOFDM modulator 16. The serial-to-parallel converter 36 takes N symbols received in a serial format and converts them into a parallel format. The variable N will be referred to herein as the blocksize of the OFDM symbol. The N parallel symbols are processed by an Inverse Discrete Fourier Transform (IDFT) stage 38, which transforms the frequency signals to the time domain. The N number of transformed symbols in the time domain will be referred to herein as samples. - A method is proposed herein to design the training symbols such that the transforms of all the sequences from the IDFT stage38 will have a constant magnitude. By maintaining a constant magnitude at the output of each of the IDFT stages 38 within their respective modulators, one of the main problems of OFDM, i.e., peak to average power ratio (PAPR), is solved. The
receiver 10 can thus more accurately estimate the channel parameters, which are used by thereceiver 10 to synchronize the received signals in the time and frequency domains, as will be described below in more detail. - The output from the IDFT stage38 is input into a
cyclic prefix inserter 40, which inserts an additional number of samples for every N samples. The number of samples inserted by thecyclic prefix inserter 40 will be referred to herein by the variable “G.” The G samples are intended to be inserted as guard intervals to separate the N adjacent data symbols from each other in time by a separation adequate to substantially eliminate Inter Symbol Interference (ISI). Thecyclic prefix inserter 40 repeats G samples from a latter portion of the N samples output from the IDFT stage 38 and inserts the G samples as a prefix to each of the data samples. Preferably, the time length of the cyclic prefix is greater than the maximum time delay of a transmitted signal across thechannel 19. Since the nature of thechannel 19 may be susceptible to a variation in the delay time from the transmittedantennas 18 to the receivingantennas 20, it may be desirable to increase, or even double, the length of cyclic prefixes of the preamble to ensure that the time delay of the channel does not exceed the time of the cyclic prefix, thereby eliminating ISI. - The G+N samples, herein referred to as an OFDM symbol, are then converted from a parallel format to a serial format using parallel-to-
serial converter 42, and then inputted to a digital-to-analog converter (DAC) 44 for conversion into analog signals. The output from theDAC 44 is input into amixer 48. Alocal oscillator 46 provides a signal having the carrier frequency to the other input of themixer 48 to up-convert the respective OFDM symbol from baseband to RF. - After the respective frame has been mixed with a carrier frequency that is set by the respective
local oscillator 46, the frame is amplified by anamplifier 50. As indicated above, one of the drawbacks to any OFDM signal is that it generally has a high PAPR. To accommodate this drawback, theamplifier 50 may be backed off to prevent it from going into its non-linear region. However, the present invention may provide certain specific sequences that can be used in order to make the PAPR minimal or unity. - Each
OFDM modulator 16 preferably comprises the same components as theOFDM modulator 16 shown in FIG. 3. Other techniques for designing theOFDM modulators 16 may be used in order to transmit the multiple frames across thechannel 19 with minimal interference. Each frame output from therespective OFDM modulator 16 is transmitted by arespective antenna 18. Theantennas 18 may be spaced apart from each other by any desirable separation. For example, the separation distance may be in a range from a few millimeters to several meters. - FIG. 4 illustrates an example of a
frame 52 that is transmitted across thechannel 19 from the transmittingantennas 18 to the receivingantennas 20. Theframe 52 comprises apreamble 54 comprising a number of training symbols NI and cyclic prefixes G. Thepreamble 54 is inserted by the pilot/training symbol inserter 32 as mentioned above. In addition, thedata frame 52 comprises adata portion 56 consisting of a plurality of OFDM data symbols N and cyclic prefixes G, which are inserted before each of the OFDM data symbols N. As previously mentioned, the pilot/training symbol inserter 32 further inserts pilot symbols (not shown) intermittently within the OFDM data symbols N. The task of thepreamble 54 and training symbols NI in the frame is to help thereceiver 10 identify the arrival of theframe 52 and hence perform time synchronization, frequency synchronization, and channel parameter estimation. - The
preamble 54, in general, consists of Q or more training symbols, wherein each training symbol has a length of G+NI samples in time. The number of samples NI is established as a certain fraction of the number of data samples N in an OFDM block such that NI=N/I, where I is an integer, such as 1, 2, 4 . . . . For example, NI may be ¼ N. If no predetermined NI has been established, the variable NI may be given the value equal to N. The training symbol length may be shorter than the length of the symbols in thedata portion 56, which has a length of G+N samples. - FIG. 5 shows a portion of the MIMO
OFDM communication system 6 of FIG. 1 along with details of a signal transmission matrix S and a received demodulated OFDM sample matrix R. The signals of thecommunication system 6 can be expressed using the equation: - R k,T×L =S k,T×Qηk,Q×L +W k,T×L
- where R is a T×L received demodulated OFDM sample matrix, η is a Q×L matrix of channel coefficients that are indicative of the characteristics of the channel across which the signals are transmitted, S is a T×Q signal transmission matrix, and W is a T×L noise matrix that corrupts and distorts the received sample matrix R. In general, T may or may not be equal to Q. However, for simplicity, T is assumed to be equal to Q herein.
- The signal transmission matrix S shown in FIG. 5 consists of Q OFDM symbols that are simultaneously transmitted from Q transmit
antennas 18 over Q or more OFDM symbol periods (Ts). For example, at a first time instance t, the OFDM symbols S1, S2, . . . SQ are transmitted from the first to theQth antennas 18. At a second time instance t+TS, the OFDM symbols SQ+1, SQ+2, . . . S2Q are transmitted from thesame antennas 18. The OFDM symbol transmissions are repeated at each time instance until all of the OFDM symbols of the matrix S have been transmitted. - During the transmission of training symbols in an initial calibration mode, the S matrix consists of Q or more training symbols, each of which is less than or equal to the length of an OFDM symbol in the time dimension. The training symbols are simultaneously transmitted from the transmitting
antennas 18 as represented by equations (1) and (2), wherein the different antennas correspond to the space dimension. - During the transmission of the data symbols, after the
communication system 6 has been calibrated, the S matrix consists of Q or more data symbols each occupying an OFDM symbol in the time dimension. The pilot/training symbol inserter 32 inserts the pilot symbols within the data symbols. The data symbols are encoded, modulated, and transmitted from the transmittingantennas 18. - Each signal transmission matrix S of Q×Q OFDM symbols are transmitted over the
communication channel 19, which naturally comprises a matrix of channel coefficients η. Typically, thecommunication channel 19 further includes characteristics that distort and degrade the transmitted signal, thereby adding a noise matrix W, before the signal transmission matrix S is received at the L receiveantennas 20. - FIG. 5 further illustrates how each of the
L receiving antennas 20 receives each of the Q transmitted signals. For example, the first receiveantenna 20 receives OFDM signals over channel impulse responses h11, h21, h31 . . . hQ1 from the first to theQth transmitting antennas 18, respectively. The term hi,j refers to the channel impulse response from the ith transmit to the jth receive antenna in the time domain. The last receiveantenna 20 receives the transmitted signals over the channel impulse responses h1L, h2L, h3L, . . . hQL from the first to theQth transmitting antennas 18, respectively. For simplicity, only the signals received at the first andlast receiving antennas 20 are shown. However, it should be understood that each receivingantenna 20 receives the signals transmitted from theQ transmitting antennas 18. - The received signals are demodulated by the
respective OFDM demodulators 22, which provide the received demodulated OFDM sample matrix R. At a time instance t, the samples R1, RQ+1, . . . R(L−1)Q+1 are received. At a next time instance t+Ts, the samples R2, RQ+2 . . . R(L−1)Q+2 are received. The samples are received at each time instance until all of the samples in the received demodulated OFDM sample matrix R are received. It should be noted that the time instances used for the matrices S and R are given the same variable, but, in essence, a delay occurs as is well known in the art. - A significant task of the
receiver 10 is to estimate the time of arrival of the transmitted signal. This process is called “time synchronization.” In addition to time synchronization, OFDM systems typically require frequency synchronization as well. Because there usually exists a certain difference between the local oscillator frequencies of the transmitter and the receiver, the received signals experience a loss of sub-carrier orthogonality, which should typically be corrected in order to avoid degradation in system performance. - FIG. 6 shows a detailed illustration of the received demodulated OFDM sample matrix R which consists of L columns and Q or more rows of OFDM symbols with respect to space and time, respectively. As shown, the matrix R consists of three dimensions, namely space, time and frequency. The frequency axis indicates the amplitude of the frequency component received at each receiving
antenna 20 from each transmittingantenna 18. Each of the matrices R and η can be seen to consist of either N matrices of dimension Q×L or Q×L vectors of length N. - In general, the training symbol length may be equal to the data symbol length. However, it is not necessary for the length of the training symbol in the preamble to be (N+G) since it is possible to estimate the characteristics of the channel even if the training symbol length is shortened to NI+G such that (N1+G)<(N+G). The variable NI may be set so as to establish a range of frequencies that may be estimated. For example, if NI=N/4, then a frequency offset of 4 sub-carrier spacings can be estimated using the training symbol. However, the range to be established may depend upon the characteristics of the channel to be estimated.
- Transmission of the training sequence of length NI corresponds to exciting every Ith sub-channel of an OFDM signal having a block size N. This means that no information is transmitted on the remaining (1−1/I)N sub-channels and the estimates of the channel for the sub-channels are derived from the ones that actually include information.
- The sub-channels of the transmit sequence that bear no information are said to be zero-padded. Alternatively, the training sequence of length NI may be generated by first modulating every Ith sub-channel of the OFDM block by a known sequence of symbols and zero padding the rest. An N-point IDFT is taken to obtain N samples in the time domain, and finally only the first NI samples along with its cyclic prefix are transmitted. At the receiver after synchronization, the samples corresponding to the training sequence of length NI are repeated I times before being demodulated by the OFDM demodulators. In a number of alternative systems, many more sub-channels are zero padded to reduce the interference between the adjacent bands and to facilitate the system implementation. For example, in the systems based on the IEEE 802.16a/b standard, a total of 56 tones or sub-carriers are zero padded.
- The training sequence structure in the frequency domain is represented by its signal transmission matrix, which is configured in such a way so as to have certain properties that aid in synchronization and channel estimation. For example, the signal transmission matrix for a 2×2 system may be of the form:
-
-
- The rows of the signal transmission matrix represent the time dimension, the columns represent the space dimension and the index k represents the frequency dimension or the corresponding sub-carrier. The
transmitter 8 may create the matrix Sk such that it is unitary. If the vectors of the training sequences are derived from the points along the unit circle in the complex domain then the signal transmission matrices Sk shown in (1) and (2) are unitary. Besides making each of the transmission matrices Sk unitary, it also facilitates the system implementation and maintains a low PAPR of the sequence structure in the time domain. This is because the signal transmission matrices in the training mode and the data mode are exactly alike, which further simplifies the system implementation. The transmission of a unitary matrix aids in parameter estimation, as is described below. - With reference again to FIG. 1, the L number of receiving
antennas 20 receive the Q number of transmitted signals and provide the received signals torespective OFDM demodulators 22, which down-convert the signal back to baseband. The L number of receivingantennas 20 are separated by a distance such that the received signals have minimum correlation and are as independent from each other as possible. The outputs from the L number ofOFDM demodulators 22 are input into adecoder 24, which combines the multiple signals and decodes them. In addition, thedecoder 24 removes any correctable noise and distortion errors, as will be described below, and outputs signals representative of the original data. - FIG. 7 illustrates an example embodiment of one of the
OFDM demodulators 22 of thereceiver 10. Received signals from the receivingantenna 20 are input into apre-amplifier 57, which amplifies the received signals to a level at which further processing may be performed. The output of thepre-amplifier 57 is connected to amixer 58. Alocal oscillator 59 provides a signal to themixer 58 having a frequency designed to demodulate the received amplified signal. The demodulated signal is then output to an analog-to-digital converter (ADC) 60, which converts the analog signals into discrete time samples. The discrete time samples are applied to asynchronization circuit 61. - An explanation will now be made to emphasize the significance of synchronization in an OFDM system. OFDM typically requires substantial synchronization in time as well as in frequency in order that transmitted signals can be recovered with adequate accuracy. Time synchronization involves determining the best possible time for the start of the received frame to closely match the start of the transmitted signal.
- Frequency synchronization involves maintaining orthogonality of the respective sub-carrier frequencies. Orthogonality refers to a condition of the sub-carrier frequencies wherein the “inner product” of the signals at different sub-carrier frequencies is zero. With respect to the inner product, reference is made, for example, to the time domain sequences s1,n wherein n=0, 1, . . . N−1 and the sub-carrier index k is equal to 1. When the sub-carrier index k is equal to 2, the time domain sequences S2,n are transmitted. The inner product is equal to Σ(S1,n)*(S2,n) wherein n=0, 1, . . . N−1. When the inner product is not equal to zero, a loss of sub-channel orthogonality may result, thereby causing Inter Carrier Interference (ICI). Since the sub-channels 20 are separated by a precise frequency difference to maintain orthogonality, any difference in frequencies between the transmitter and the receiver local oscillators may cause a loss of sub-channel orthogonality. The
synchronization circuit 61 corrects this loss of sub-channel orthogonality by finding an estimate of the difference between the frequencies of thelocal oscillators 46 of thetransmitter 8 and the frequencies of thelocal oscillators 59 of thereceiver 10. Thesynchronization circuit 61 further corrects these frequency difference estimates. - The frequency and time synchronized information is provided to the
cyclic prefix remover 62, which removes the cyclic prefixes inserted between each block of N symbols. The blocks of N samples are then serial-to-parallel converted using serial-to-parallel converter 63 and the parallel signals are input to a Discrete Fourier Transform (DFT)stage 64, which converts the time domain samples back to the frequency domain, thus completing synchronization and demodulation by theOFDM demodulators 22. - Referring again to FIG. 1, the L number of demodulated signals from each of the L number of
OFDM demodulators 22 are then input into thedecoder 24, which processes the demodulated signals. Thedecoder 24 may be configured in the manner shown in the example embodiment of FIG. 8. Thedecoder 24 comprises a space-time processor 110 and aparameter estimator 112. Both the space-time processor 110 andparameter estimator 112 receive the signals from each of the L number ofOFDM demodulators 22. - An output from the
parameter estimator 112 is input into asymbol demapper 116 and a set of outputs is input into the space-time processor 110. The output of the space-time processor 110 is converted from parallel to serial by a parallel-to-serial converter 114 and then input to thesymbol demapper 116, which maps the symbols from the predetermined alphabet back to the data bits. The output from thesymbol demapper 116 is input into achannel decoder 118. Thechannel decoder 118 decodes the data symbols by checking the parity that was added to the symbols prior to transmission. Thus, thechannel decoder 118 detects and corrects errors in the data symbols and outputs the data in its original form. There can be an exchange of information between theparameter estimator 112,symbol demapper 116, andchannel decoder 118 to create a feedback loop. If thechannel decoder 118 detects too many errors in the training symbol such that correction of the errors is no longer possible, then an “excessive-error” indication is made to theparameter estimator 112, which adjusts and corrects its estimates. - An explanation of the
parameter estimator 112 will now be made. Theparameter estimator 112 estimates characteristics of the channel across which the communication signals are transmitted. These channel characteristics or parameters may include, for example, the channel coefficient matrix η, signal to noise ratio (SNR), noise variance, time correlation, and frequency correlation. Having knowledge of the unique channel parameters enables thereceiver 10 to compensate for the various distortions introduced by the channel. Since thereceiver 10 does not have prior knowledge of the channel parameters, theparameter estimator 112 calculates an estimation of the channel parameters, based on the training sequence transmitted by thetransmitter 8. However, because of the complex processing involved with thesynchronization circuit 61 to provide time and frequency synchronization and frequency offset estimation, there is a need to design algorithms of theparameter estimator 112 having relatively low complexity to adhere to stringent timing constraints. On the other hand, there is a need for the algorithms to be highly effective for accurately estimating the channel parameters. - Before performing parameter estimation, the received OFDM samples belonging to the training symbols of length NI, and a copy of the transmitted training sequences of length NI are repeated I times and their N-point FFT are taken to convert the received OFDM sample matrix R and the OFDM signal transmission matrix S to have their dimension in the frequency domain to be N.
- FIG. 9 shows a first embodiment of a method performed by the
parameter estimator 112 for calculating channel estimates. Theparameter estimator 112 derives its estimates using a Least Squares (LS) method. If a certain number T of training symbols are transmitted from all the Q transmit antennas, where T≧Q, then the LS estimates are obtained as - {overscore (η)}k=(S k H S k)−1 S k H ·R k k=0,1, . . . , N I−1
- where the signal transmission matrix S for each of the sub-carriers has T rows and Q columns. The channel estimates so obtained minimize the error between the estimated channel coefficient matrix and the actual channel coefficient matrix for each tone. It should be noted that the NI channel coefficient matrices so obtained are only representative of those tones that were excited in the transmitted sequence. The channel coefficient matrix for all the other tones are set to zero.
- Further, if LS method is used along with the use of the signal transmission matrices such as the ones shown in (1) and (2), only Q OFDM symbols of a generalized length NI are needed to estimate the channel coefficients accurately. In absence of any noise, the
parameter estimator 112 provides the exact estimates of the channel coefficient matrices. This type of parameter estimator is called a zero-forcing estimator. Also, by using the LS method, the hardware complexity is reduced considerably since the same circuitry can be used for the data symbols as well as the training symbols. - Hence, if the
transmitter 8 creates the transmitting matrices S such that the matrices are unitary as described above, then the preamble may be formed having only Q symbols. By using only Q symbols of any generalized length NI, useful bandwidth is preserved for the transmission of data. Furthermore, the training symbols may be created having fewer than Q symbols, and may even be created having one symbol. - The method of FIG. 9 comprises a first step (block120) for calculating coarse channel estimates of the channel coefficient matrix using an LS method and/or a Zero forcing method, if the Sks are unitary. The coarse channel estimates may be calculated by a formula such as:
- {overscore (η)}k =S k H ·R k =S k −1 ·R k=ηk +{overscore (W)} k k=0,1, . . . , N I−1
- where Wk=(Sk −1)(Wk).
- An aim of the channel estimation algorithm is to estimate the channel coefficients for all the sub-carriers. However, when NI is not equal to N, the channel coefficients are available for only NI sub-carriers since the received OFDM training symbol of length NI was repeated I times before passing through the
DFT stage 64. To estimate the sub-carriers that were not excited, a frequency domain interpolation procedure is performed, as indicated byblock 124. When the channel comprises a bandwidth that is substantially coherent, a simple linear interpolation scheme may be used to estimate the unexcited sub-carriers. Of course, when I is high, more sub-carriers are estimated from less information, which results in an increase in the mean square error (MSE) in the channel estimates. In the case of increased MSE, a more complex interpolation scheme may be used. Therefore, there is a tradeoff between the greater training sequence overhead to minimize the estimation errors, allowing a simpler interpolation scheme to be used, and a lesser training sequence overhead to avoid taking up useful bandwidth, requiring a more complex interpolation scheme. -
-
- where 1 is less than or equal to i which is less than or equal to Q and 1 is less than or equal to j which is less than or equal to L. The Q*L number of length-N vectors are then made to go through a windowing operation, which reduces the effect of noise variations in the channel and ICI. The windowing operation recovers the time domain fine channel estimates whereby:
-
- The reduction of the MSE by the previous steps provides accurate estimates of the channel parameters. The
parameter estimator 112 outputs these fine channel estimates to the space-time processor 110 in order to compensate for the unique channel parameters. Other than the method mentioned above to reduce the MSE in LS channel estimates, one can follow a number of different methods for reducing MSE, such as performing a smoothing procedure in the frequency domain, a Linear Prediction (LP) procedure, a method where decisions are fed back to the parameter estimator, a decision directed update procedure, etc. - Alternative to the embodiment of FIG. 9, another embodiment for calculating fine channel estimates is illustrated in FIG. 10. This embodiment refers to the case mentioned earlier when a large number of sub-carriers of the OFDM symbols are zero padded to facilitate the system implementation. Again, it is assumed that the signal transmission matrix S may or may not be unitary and the training sequence includes Q training symbols. In this alternative embodiment, a first step (block130) includes zero padding the recommended sub-carriers in the training sequence. For example, in a system that meets the IEEE 802.16a/b standard, sub-carriers at DC and 55 others at high frequencies are set to zero. This sub-carrier elimination step simplifies the system implementation and further avoids adjacent channel interference. For such systems, the above-mentioned method of MSE reduction typically cannot be applied directly since the channel estimates are not available for the zero-padded sub-carriers. For such systems, the sub-carrier frequencies that are eliminated may be initially estimated using frequency domain extrapolation on the existing LS estimates. The channel estimates at DC can be calculated by taking an average of the channel estimates for the positive and negative frequencies. The estimates of the eliminated sub-carrier frequencies are used to reduce the MSE in the channel estimates but are otherwise ignored since no data is transmitted on these sub-carriers. Once channel estimates for all the sub-carriers are available, the procedure for MSE reduction mentioned above, along with a procedure for noise variance estimation that is described below, can be implemented. In a later step, the fine channel estimates for the zero-padded sub-carriers may be discarded.
- After the zero-padding of tones, represented by
step 130 in FIG. 10, the coarse channel estimates are calculated using the LS method and/or Zero forcing estimation, as indicated byblock 134. This step is identical to thecorresponding step 120 of FIG. 9.Block 136 includes the step of performing interpolating in the frequency domain. This step is identical to step 124 of FIG. 9. When frequency domain interpolation has been completed, the method of FIG. 10 proceeds to block 138 where a frequency domain extrapolation takes place. Frequencies at the low and high ends are extrapolated based on the existing middle frequencies in order to arrive at the estimates for these frequencies. - At this point, a reduction in the MSE is calculated, as indicated in
block 140. All of the frequencies in the bandwidth, including the eliminated frequencies are used in the reduction of the MSE. Otherwise,step 140 is the same asstep 126 of FIG. 9. Since only the MSE-reduced estimates of a selected range of transmitted sub-carrier frequencies are used, the unused frequencies outside the transmission bandwidth are discarded, as indicated inblock 142. Thus, the fine estimates of the channel parameters having been obtained at the end ofblock 142, theparameter estimator 112 outputs the fine channel estimates to the space-time processor 110. - In addition to the estimation of channel parameters, the
parameter estimator 112 may further calculate estimates of the “noise variance,” which is a parameter representing the power of the extraneous unwanted noise present in the signal. The noise variance is based on the coarse channel estimates and can be obtained for each of the receivingantennas 20. - FIG. 11 shows an embodiment of a noise variance estimation method.
Block 150 indicates a step wherein noise variance estimates for each of the receive antennas can be calculated. Assuming that the signal transmission matrices S are unitary, the noise variance estimates can be obtained directly from the coarse channel estimates using the following formula: - where gij,n is the coefficient of the time domain coarse channel estimates for the ith transmit and jth receive antennas obtained from the
parameter estimator 112. The noise variance is calculated for each of the j receive antennas. - In case the signal transmission matrix is not unitary, then the noise variance estimation is a little more complex. This alternative noise variance estimation method is shown in FIG. 12. A noise term is determined by subtracting the matrices of the fine channel estimates from the matrices of the coarse channel estimates, whereby the coarse channel estimates and fine channel estimates are obtained from the
parameter estimator 112 as described above with reference to the channel estimation methods of FIGS. 9 and 10. Calculation of the noise terms is shown usingblock 152 and can be represented using the following equation: - G′ k={overscore (η)}k−{circumflex over (η)}k , k=0,1, . . . , N−1.
- The next step includes multiplying the matrices Gk′ with the signal transmission matrices Sk as is represented by
block 154 and as is given by the following equation: - G k =S k G′ k , k=0,1, . . . , N−1.
- The next step is to convert the frequency domain coefficients to the time domain, which is represented using
block 156 and can be described using the following equation. - w ij =IDFT{G ij} 1≦i≦Q, 1≦j≦L
-
- The
parameter estimator 112 may include software stored in memory, wherein the software may include one or more separate programs, each of which comprises an ordered listing of executable instructions for implementing logical functions. In the example of FIGS. 9-12, the software may include the parameter estimator system in accordance with the present invention and a suitable operating system (O/S). Examples of suitable commercially available operating systems are as follows: a Windows operating system available from Microsoft Corporation; a Netware operating system available from Novell, Inc.; a Macintosh operating system available from Apple Computer, Inc.; a UNIX operating system available from the Hewlett-Packard Company, Sun Microsystems, Inc., or AT&T Corporation; a LINUX freeware operating system that is readily available on the Internet; a run time Vxworks operating system available from WindRiver Systems, Inc.; an appliance-based operating system, such as that implemented in a handheld computer or personal data assistant (PDA) (e.g., PalmOS available from Palm Computing, Inc. or Windows CE available from Microsoft Corporation). The O/S essentially controls the execution of other computer programs, such as the parameter estimation system, and provides scheduling, input-output control, file and data management, memory management, and communication control and related services. - The
parameter estimator 112 can be implemented in hardware, software, firmware, or a combination thereof. In the embodiments of the present invention, theparameter estimator 112 can be implemented in software or firmware that is stored in a memory and that is executed by a suitable instruction execution system. If implemented in hardware, as in an alternative embodiment, the synchronization system can be implemented with any or a combination of the following technologies, which are all well known in the art: a discrete logic circuit having logic gates for implementing logic functions upon data signals, an application specific integrated circuit (ASIC) having appropriate combinational logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), digital signal processor (DSP), etc. - It should be emphasized that the above-described embodiments of the present invention are merely possible examples of implementations, merely set forth for a clear understanding of the principles of the invention. Many variations and modifications may be made to the above-described embodiments of the invention without departing substantially from the principles of the invention. All such modifications and variations are intended to be included herein within the scope of this disclosure and protected by the following claims.
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